Sample applications

(Ran Nathan’s Movement Ecology Lab, The Hebrew University of Jerusalem)

Last update: September 2014

This project explores the movements of vultures over wide spatial and temporal scales. To this end, we have used cutting-edge technology and tracked free-ranging vultures in two distinct ecosystems at levels of accuracy and durations that were unachievable until recently. In particular, we deploy GPS tags and obtain a rich data set (location information at a 1 second to 10 minute interval), together with complementary behavioral data from field observations and from accelerometer sensors embedded in the tags. Other related information, such as wind conditions and terrain elevation, is obtained from online databases and atmospheric models.

Our team was able to capture and track 87 adult griffon vultures (Gyps fulvus) in southern Israel (324 ± 27 days [mean ± S.E.]), 12 white-backed vultures (Gyps africanus) and three lappet-faced vultures (Torgos tracheliotus) in Namibia for similar periods. Within the framework of the movement ecology framework, we examined the link between the internal state and movement patterns by exploring the effect of hunger on vultures’ movement and the phenomenon of long-range forays; and the link between the external factors and navigation capacity in comparing search efficiency between species, social information transfer, resource predictability and age-related variation in thermal soaring performance.

Insights from these projects include a few complementary aspects involving methodology, applied science (vulture conservation), and basic science (movement ecology). Regarding the methodological aspect, we developed new analytical tools for identifying animal behavioral modes from analyses of the acceleration data, calibrated by field observations (Regarding the conservation aspect, the data enabled us to quantify the seasonal changes in vulture movement patterns. Regarding the basic ecological research aspect, we were able to identify factors responsible for differences in search efficiency between the lappet-faced vulture and the white-backed vulture (such as visual acuity and wing morphology), to identify age related differences in the tendency to migrate, to how climatic conditions affect the soaring behavior of vultures, to evaluate the impact of provisioning vulture feeding stations on the behavior and viability of the griffon vulture population, and to identify rare long-range forays performed by the griffon vulture. Our data shows that these forays cannot be explained by simple optimal foraging criteria. Rather, the actual flight data suggested that these forays represent unsuccessful dispersals attempts during which individuals were likely searching for new partners or colonies. Beyond this intriguing finding, the work addresses a general ongoing debate regarding the causes for the common observation that animal movements result in fat-tailed step-size distribution and that vultures’ movements are a product of distinct modes, operating at different spatial scales.

Understanding movement patterns and their implications on fitness in a long-distance avian migrant: the White Stork (Ciconia ciconia)

Shay Rotics and Sondra Feldman Turjeman

(Ran Nathan’s Movement Ecology Lab, The Hebrew University of Jerusalem)

The phenomenon of seasonal, inter-continental migration of birds has fascinated mankind from time immemorial. Using cutting-edge GPS telemetry devices and advanced analysis tools, We aim to address key questions about migration and fitness that have, thus far, been unapproachable. We track 170 white storks, Ciconia ciconia, of different sex and age with solar-powered GPS transmitters and quantify their movement, behavior, physiology, reproductive success and survival throughout the annual cycle. High resolution migration tracks are being linked to environmental variables such as wind, thermals, temperature and vegetation productivity (NDVI) in order to elucidate how the environment affects movement. In turn, we aim to understand survival and breeding success of a model migrant as the consequence of individual movement decisions in space and time.

This study is part of an ongoing project which explores the interaction between social behavior and landscape factors affecting the space use patterns of the reintroduced Asiatic wild ass (Equus hemionus ssp.) in the Negev desert, Israel. E. hemionus is a non-ruminant, mid-sized equid (approximately 200 kg) inhabiting desert and mountain steppe. It is defined as an endangered species by the IUCN. We studied E. hemionus movement patterns. Specifically, In terms of the movement ecology framework, we investigated the effect of external factors—resource distribution and landscape features—on movement displacements, habitat selection and space use patterns. Because in arid environments, resources (e.g. water and forage) are limited and scarcely distributed, we examined the link between resource distribution and the E. hemionus temporal movement and recursion patterns (i.e. returns to specific patches) on seasonal and daily scales.

GPS satellite collars were attached to five E. hemionus individuals (four males and one female) captured in the wild near the main water source in the Negev Highlands. Individuals' GPS location data were obtained every hour since August 2013. During winter (January) and summer (July-August) 2014, additional location data was collected every 15 minutes during a period of 6-8 days for each collared individuals. Data collection allowed the computation of FMEs (Fundamental Movement Elements) such as inter-locations velocity and angle performed and the analysis of individuals’ movement displacements and recursion durations. GIS layers of vegetation cover, hydrologic network, slopes and aspects were used to characterize recursion patterns, home range features and habitat selection. The analyses were performed according to seasonal and circadian scales in order to examine temporal variability.

The summer mean hour distance displacements of E. hemionus (376.67 m ± SE 55.81) was significantly higher than in winter (311.46 m ± SE 39.60); (F1,211 = 15.488; P < 0.0001). E. hemionus mainly moved during the summer nights (mean displacement 578.66 m ± SE 171.03) and during the winter days (343.30 m ± SE 63.17). Their habitat selection temporal patterns differed significantly between the seasons as well as throughout the day: they significantly spent most of the nights in wadies during the summer where vegetation cover is high (as indicated by the NDVI scores, F23,92 = 3.002, P < 0.0001) and the slope is low (F23,92 = 1.816, P < 0.0244). During the days, they selected mountain ridges (F23,211 = 2.855, P < 0.0001) facing the northern aspect (F1,211 = 65.810, P < 0.0001), probably as a thermoregulation strategy ("cooling spots"). Individuals spent more time within a site during the summer days on the mountain ridges, than they spent within sites during the summer nights (in wadies) (Chisq = 758.48, Df = 23, P < 0.0001). Median recursion time (i.e. the time to return to a site/patch) was significantly shorter in summer, 1.83 days (95% confidence interval: 1.79 - 1.92 days) than in winter, 7.46 days (95% confidence interval: 6.79 - 8.29). Further analyses should test our prediction that the winter recursion sites are mainly resource patches, for which a delay in the recursion time is needed for "resource recovery" (Bar-David et al. 2009), while the summer recursion sites are mostly "cooling spots" which can be used on a daily basis.

We developed a new approach for characterizing animals' temporal space use dynamics which is based on the analysis of individuals' recursive movement patterns. This approach provides a higher resolution information than the classical home range analyses. The results obtained in this study enabled us to quantify the circadian and seasonal changes in wild ass movement patterns; to identify landscape features which affect the way individuals use and select habitats within their home ranges; and to gain information that could be applied for the conservation of E. hemionus in the Negev desert.

Bacterial predator-prey dynamics in micro-scale patchy landscapes

Soil is a microenvironment with a fragmented (patchy) spatial structure in which many bacterial species interact. Here we explore the interaction between the predatory bacterium Bdellovibrio bacteriovorus and its prey Escherichia coli in microfabricated landscapes. We ask how fragmentation influences predator-prey dynamics at the microscale, and compare two landscape geometries: a patchy landscape and a continuous landscape. By following the dynamics of prey populations with high spatial and temporal resolution for many generations, we find that in both geometries the predator drives the prey towards extinction, yet the dynamics differ between landscapes. In comparison to the continuous landscape, the variation in predation dynamics is twice as large in the patchy landscape and is correlated over shorter length scales. The patchy landscape is found to behave non-fragmented in various respects, e.g., temporal correlations extend far beyond the single patch, and metapopulation phenomena such as patch rescue and increased lifetime of the overall prey population are not observed. The concurrence of fragmented and continuous characteristics in microscale patchy landscapes may be explained by the properties of bacteria in microscale systems: a population exists in a dynamic superposition of sessile (surface-bound) and motile (planktonic) lifestyles, migration through narrow corridors is efficient, and populations attain high densities. High mobility and density reduce stochastic fluctuations, increase predation efficiency, and enhance spatial correlations. Furthermore, we observe that surface-bound microcolonies may "clog" the connections between patches, which promotes heterogeneity.

Relevant Articles

Hol et al, under review

Multi-Sensing Navigation from the Bat's Point of View - Using a Drone

Niv Dobzinski and Yossi Yovel

(Tel Aviv University)

Bats are among the best navigators in the mammalian world, often navigating over dozens of kilometers nightly and up to thousands of kilometers during migration. Although echolocation is the most studied sensory modality in most bats, it is definitely not the only one and probably not the most important one for long range navigation. The aim of this study is to identify and characterize other senses that are being used for longer-range orientation and navigation by studying the multiple sources of potential sensory inputs that are available for a navigating bat from the 'point of view' of the bat.

We use a new technology – a hexacopter drone flying platform. Multi-rotor Drones are highly stable flying platforms and are capable of flying very accurately in any desired course and holding position in any desired location in space. The unique flight characteristics of the drones not only enables them to do tasks that aircraft models are not capable of e.g. fly in a vertical course, or at low speeds, but also to take off and land in almost any terrain without the need of a runway. The drone will be mounted with multiple sensors, covering all four sensory modalities that the bat could potentially use. The drown will then be flown in known bat trajectories, while acquiring multiple sensory inputs that the bat could potentially use, which enable us to simultaneously test all four main sensory modalities that might contribute to bat navigation: vision, magnetosensing, olfaction and echolocation.

Data analysis will aim to find correlations between the different types of sensory input and the decisions made by the navigating bat (e.g. turning, slowing down, etc.). For example, large changes in the magnetic field which are correlated with sharp turns of the bat suggest the use of magnetic navigation.

Finally, based on our findings, we hope to develop a sensorimotor model that can explain long range multimodal navigation and can be later used for guiding artificial human navigating technologies (e.g. a drone). We have recently shown how the sensory input (vision and echolocation) acquired by a bat flying a short distance can be integrated using a control model to guide a flight. Our model, which uses sensory input and outputs motor commands, was highly successful in explaining the actual flight trajectory flown by a bat. We thus aim to adjust this model, making it suitable for guiding long-range navigation over dozens of kilometers based on the sensory input that we will find. For example, a visual based model will extract the visual input available to the bat (e.g. distal city lights) and will translate them into motor commands that will guide the bat along its path.